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New Generation Database Systems: IR Systems and the Grid/Cloud

New Generation Database Systems: IR Systems and the Grid/Cloud. University of California, Berkeley School of Information IS 257: Database Management. Lecture Outline. XML and DBMS Cheshire II as XML Database The Grid and DBMS The Grid Data Grids Grid-based DBMS. Lecture Outline.

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New Generation Database Systems: IR Systems and the Grid/Cloud

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  1. New Generation Database Systems: IR Systems and the Grid/Cloud University of California, Berkeley School of Information IS 257: Database Management

  2. Lecture Outline • XML and DBMS • Cheshire II as XML Database • The Grid and DBMS • The Grid • Data Grids • Grid-based DBMS

  3. Lecture Outline • XML and DBMS • Cheshire II as XML Database • The Grid and DBMS • The Grid • Data Grids • Grid-based DBMS

  4. Standards: XML/SQL • That table can be mapped to: <EMPLOYEE> <row><EMPNO>000020</EMPNO> <FIRSTNAME>John</FIRSTNAME> <LASTNAME>Smith</LASTNAME> <BIRTHDATE>1955-08-21</BIRTHDATE> <SALARY>52300.00</SALARY> </row> <row> … etc. …

  5. XML to Relational Database Mapping Bhavin Kansara The following slides are adapted from: Slide from Bhavin Kansara

  6. Introduction • XML/relational mapping means data transformation between XML and relational data models • XML documents can be transformed to relational data models or vice versa. • Mapping method is the way the mapping is done Slide from Bhavin Kansara

  7. DTD graph Slide from Bhavin Kansara

  8. Inlined DTD graph Slide from Bhavin Kansara Given a DTD graph, a node is inlinable if and only if it has exactly one incoming edge and that edge is a normal edge.

  9. Inlined DTD graph Slide from Bhavin Kansara

  10. Generated Database Schema Slide from Bhavin Kansara

  11. Data Mapping Slide from Bhavin Kansara XML file is used to insert data into generated database schema Parser is used to fetch data from XML file.

  12. Summary Slide from Bhavin Kansara Simplify DTD Create DTD graph from simplified DTD Create inlined DTD graph from DTD graph Use inlined DTD graph to generate database schema Insert values from XML file into generated tables

  13. Issues • So, we can convert the XML to a relational database, but can we then export as an XML document? • This is equally challenging • But MOSTLY involves just re-joining the tables • How do you store and put back the wrapping tags for sets of subelements? • Since the decomposition of the DTD was approximate, the output MAY not be identical to the input

  14. Anatomy of a Native XML database • The next set of slides (available on the class web site) come from George Feinberg of SleepyCat Software • SleepyCat is now part of Oracle

  15. Further comments on NXD • Native XML databases are most often used for storing “document-centric” XML document • I.e. the unit of retrieval would typically be the entire document and not a particular node or subelement • This supports query languages like Xquery • Able to ask for “all documents where the third chapter contains a page that has boldfaced word” • Very difficult to do that kind of query in SQL

  16. XML-Based IR - Cheshire II • I thought I would take a little time to talk about how the Cheshire system (that I have been working for nearly 20 years) uses XML, since it has some similarities (and many differences) to XML database systems • Cheshire II (and Cheshire 3) are document-centric and involve parsing the XML for the purposes of indexing (and sometimes for retrieval of partial documents)

  17. Cheshire II SGML/XML Support • Underlying native format for all data is SGML or XML • The DTD defines the file format for each file • Full SGML/XML parsing • SGML/XML Format Configuration Files define the database • USMARC DTD and MARC to SGML conversion (and back again) • Access to full-text via special SGML/XML tags

  18. SGML/XML Support • Example XML record for a DL document <ELIB-BIB> <BIB-VERSION>ELIB-v1.0</BIB-VERSION> <ID>756</ID> <ENTRY>June 12, 1996</ENTRY> <DATE>June 1996</DATE> <TITLE>Cumulative Watershed Effects: Applicability of Available Methodologies to the Sierra Nevada</TITLE> <ORGANIZATION>University of California</ORGANIZATION> <TYPE>report</TYPE> <AUTHOR-INSTITUTIONAL>USDA Forest Service</AUTHOR-INSTITUTIONAL> <AUTHOR-PERSONAL>Neil H. Berg</AUTHOR-PERSONAL> <AUTHOR-PERSONAL>Ken B. Roby</AUTHOR-PERSONAL> <AUTHOR-PERSONAL>Bruce J. McGurk</AUTHOR-PERSONAL> <PROJECT>SNEP</PROJECT> <SERIES>Vol 3</SERIES> <PAGES>40</PAGES> <TEXT-REF>/elib/data/docs/0700/756/HYPEROCR/hyperocr.html</TEXT-REF> <PAGED-REF>/elib/data/docs/0700/756/OCR-ASCII-NOZONE</PAGED-REF> </ELIB-BIB>

  19. SGML Support • Example SGML/MARC Record <USMARC Material="BK" ID="00000003"><leader><LRL>00722</LRL><RecStat>n</RecStat> <RecType>a</RecType><BibLevel>m</BibLevel><UCP></UCP><IndCount>2</IndCount> <SFCount>2</SFCount><BaseAddr>00229</BaseAddr><EncLevel> </EncLevel> <DscCatFm></DscCatFm><LinkRec></LinkRec><EntryMap><FLength>4</Flength><SCharPos> 5</SCharPos><IDLength>0</IDLength><EMUCP></EMUCP></EntryMap></Leader> <Directry>001001400000005001700014008004100031010001400072035002000086035001700106100001900123245010500142250001100247260003200258300003300290504005000323650003600373700002200409700002200431950003200453998000700485</Directry><VarFlds> <VarCFlds><Fld001>CUBGGLAD1282B</Fld001><Fld005>19940414143202.0</Fld005> <Fld008>830810 1983 nyu eng u</Fld008></VarCFlds> <VarDFlds><NumbCode><Fld010 I1="Blank" I2="Blnk"><a>82019962 </a></Fld010> <Fld035 I1="Blank" I2="Blnk"><a>(CU)ocm08866667</a></Fld035><Fld035 I1="Blank" I2="Blnk"><a>(CU)GLAD1282</a></Fld035></NumbCode><MainEnty><Fld100 NameType="Single" I2=""><a>Burch, John G.</a></Fld100></MainEnty><Titles><Fld245 AddEnty="Yes" NFChars="0"><a>Information systems :</a><b>theory and practice /</b><c>John G. Burch, Jr., Felix R. Strater, Gary Grudnitski</c></Fld245></Titles><EdImprnt><Fld250 I1="Blank" I2="Blnk"><a>3rd ed</a></Fld250><Fld260 I1="" I2="Blnk"><a>New York :</a><b>J. Wiley,</b><c>1983</c></Fld260></EdImprnt><PhysDesc><Fld300 I1="Blank" I2="Blnk"><a>xvi, 632 p. :</a><b>ill. ;</b><c>24 cm</c></Fld300></PhysDesc><Series></Series><Notes><Fld504 I1="Blank" I2="Blnk"><a>Includes bibliographical references and index</a></Fld504></Notes><SubjAccs><Fld650 SubjLvl="NoInfo" SubjSys="LCSH"><a>Managementinformation systems.</a></Fld650> ...

  20. SGML Support • Mini-TREC document… <DOC> <DOCNO>FT931-3566</DOCNO> <PROFILE>_AN-DCPCCAA3FT</PROFILE> <DATE>930316 </DATE> <HEADLINE> FT 16 MAR 93 / Italy's Corruption Scandal: Magistrates hold key to unlocking Tangentopoli - They will set the investigation agenda </HEADLINE> <BYLINE> By ROBERT GRAHAM </BYLINE> <TEXT> OVER the weekend the Italian media felt obliged to comment on a non-event. No new arrests had taken place in any of the country's ever more numerous corruption scandals which centre on the illicit funding of political parties ... </TEXT> <XX> …

  21. … Companies:- </XX> <CO>Ente Nazionale Idrocarburi. Ente Nazionale per L'Energia Electtrica. Ente Partecipazioni E Finanziamento Industria Manifatturiera. IRI Istituto per La Ricostruzione Industriale. </CO> <XX> Countries:- </XX> <CN>ITZ Italy, EC. </CN> <XX> Industries:- </XX> <IN>P9222 Legal Counsel and Prosecution. P91 Executive, Legislative and General Government. P13 Oil and Gas Extraction. P9631 Regulation, Administration of Utilities. P6719 Holding Companies, NEC. </IN> <XX> Types:- </XX> …

  22. … <TP>CMMT Comment &amp; Analysis. GOVT Legal issues. </TP> <PUB>The Financial Times </PUB> <PAGE> London Page 4 </PAGE> </DOC>

  23. SGML/XML Support • Configuration files for the Server are also SGML/XML: • They include tags describing all of the data files and indexes for the database. • They also include instructions on how data is to be extracted for indexing and how Z39.50 attributes map to the indexes for a given database.

  24. Cheshire Configuration Files <!-- ******************************************************************* --> <!-- ************************* TREC INTERACTIVE TEST DB **************** --> <!-- ******************************************************************* --> <!-- This is the config file for the Cheshire II TREC interactive Database --> <DBCONFIG> <DBENV>/projects/is240/GroupX/indexes </DBENV> <!-- --> <!-- TREC TEST DATABASE FILEDEF --> <!-- --> <!-- The Interactive TREC Financial Times datafile --> <FILEDEF TYPE=SGML> <DEFAULTPATH>/projects/is240/GroupX </DEFAULTPATH> <!-- filetag is the "shorthand" name of the file --> <FILETAG> trec </FILETAG> <!-- filename is the full path name of the main data directory --> <FILENAME> /projects/is240/ft </FILENAME> <CONTINCLUDE> /projects/is240/ft.CONT </CONTINCLUDE> <!-- fileDTD is the full path name of the file's DTD --> <FILEDTD> /projects/is240/TREC.FT.DTD </FILEDTD> <!-- assocfil is the full path name of the file's Associator --> <ASSOCFIL> ft.assoc </ASSOCFIL> <!-- history is the full path name of the file's history file --> <HISTORY> cheshire_index/TESTDATA.history </HISTORY> …

  25. <!-- The following are the index definitions for the file --><INDEXES><!-- ******************************************************************* --><!-- ************************* DOC NO. ********************************* --><!-- ******************************************************************* --><!-- The following provides document number access. --><INDEXDEF ACCESS=BTREE EXTRACT=KEYWORD NORMAL=NONE PRIMARYKEY=IGNORE><INDXNAME> cheshire_index/trec.docno.index </INDXNAME><INDXTAG> docno </INDXTAG><INDXMAP> <USE> 12 </USE><struct> 1 </struct> </INDXMAP><INDXMAP> <USE> 12 </USE><struct> 2 </struct> </INDXMAP><INDXMAP> <USE> 12 </USE><struct> 6 </struct> </INDXMAP><INDXKEY><TAGSPEC><FTAG>DOCNO </FTAG></TAGSPEC> </INDXKEY> </INDEXDEF>…

  26. <!-- ******************************************************************* --> <!-- ************************* TOPIC *********************************** --> <!-- ******************************************************************* --> <!-- The following is the primary index for probabilistic searches --> <!-- It includes headlines, datelines, bylines, and full text --> <INDEXDEF ACCESS=BTREE EXTRACT=KEYWORD_PROXIMITY NORMAL=STEM> <INDXNAME> cheshire_index/trec.topic.index </INDXNAME> <INDXTAG> topic </INDXTAG> <INDXMAP> <USE> 29 </USE><POSIT> 3 </posit> <struct> 6 </struct> </INDXMAP> <INDXMAP> <USE> 29 </USE><RELAT> 102 </RELAT><POSIT> 3 </posit> <struct> 6 </struct> </INDXMAP> … <STOPLIST> cheshire_index/topicstoplist </STOPLIST> <INDXKEY> <TAGSPEC> <FTAG>HEADLINE </FTAG> <FTAG>DATELINE </FTAG> <FTAG>BYLINE </FTAG> <FTAG>TEXT </FTAG> </TAGSPEC> </INDXKEY> </INDEXDEF>

  27. Cluster Definitions <!-- ************************* CLUSTER ********************************* --> <!-- *********************** DEFINITIONS ******************************* --> <CLUSTER> <clusname> classcluster </clusname> <cluskey normal=CLASSCLUS> <tagspec> <FTAG>FLD950 </FTAG> <s> ^a </s> </tagspec> </cluskey> <stoplist> /usr3/cheshire2/data2/clasclusstoplist </stoplist> <clusmap> <from> <tagspec> <ftag>FLD245</ftag><s>^[ab]</s> <ftag>FLD440</ftag><s>^a</s> <ftag>FLD490</ftag><s>^a</s> <ftag>FLD830</ftag><s>^a</s> <ftag>FLD740</ftag><s>^a</s> </tagspec></from> <to> <tagspec> <ftag>titles</ftag> </tagspec></to> <from> <tagspec> <ftag>FLD6..</ftag><s>^[abcdxyz]</s> </tagspec></from> <to> <tagspec> <ftag>subjects</ftag> </tagspec></to> <summarize> <maxnum> 5 </maxnum> <tagspec> <ftag>subjsum</ftag> </tagspec></summarize> </clusmap> </CLUSTER>

  28. Component Definitions <COMPONENTS> <COMPONENTDEF> <COMPONENTNAME> TESTDATA/COMPONENT_DB1 </COMPONENTNAME> <COMPONENTNORM>NONE</COMPONENTNORM> <COMPSTARTTAG> <TAGSPEC> <FTAG>mainenty </FTAG> <FTAG>titles </FTAG> </TAGSPEC> </COMPSTARTTAG> <COMPENDTAG> <TAGSPEC><FTAG>Fld300 </FTAG></TAGSPEC> </COMPENDTAG> <COMPONENTINDEXES> <!-- First index def --> <INDEXDEF ACCESS=BTREE EXTRACT=KEYWORD NORMAL=NONE> <INDXNAME> TESTDATA/comp1index1.author … </INDEXDEF> </COMPONENTDEF> </COMPONENTS>

  29. Result Formatting (Display) <DISPOPTIONS> KEEP_ENTITIES </DISPOPTIONS> <DISPLAY> <FORMAT NAME="B" OID="1.2.840.10003.5.105" DEFAULT> <convert function="TAGSET-G"> <clusmap> <from> <tagspec> <ftag>DOCNO</ftag> </tagspec></from> <to> <tagspec> <ftag>28</ftag> </tagspec></to> <from> <tagspec> <ftag>#DOCID#</ftag> </tagspec></from> <to> <tagspec> <ftag>5</ftag> </tagspec></to> </clusmap> </convert> </FORMAT> </DISPLAY>

  30. Indexing • Any SGML/XML tagged field or attribute can be indexed: • B-Tree and Hash access via Berkeley DB (Sleepycat) • Stemming, keyword, exact keys and “special keys” • Mapping from any Z39.50 Attribute combination to a specific index • Underlying postings information includes term frequency for probabilistic searching. • SGML may include address of full-text for indexing • New indexes can be easily added, or old ones deleted

  31. Database Storage • All data stored as SGML/XML flat text files or in a BerkeleyDB database • File format is defined though SGML/XML DTD (also flat text file) or XML Schema • “Associator” files provide indexed direct access to each record in SGML/XML files. • Contain offset and record length for each “record” • Associators can be built to index any conformant document in a directory sub-tree

  32. Database Storage Remote RDBMS Config File Page Data File Index File Postings File History File Index File SGML/XML File DTD File Associator File Cluster File Index File Prox data File Associator File

  33. Client/Server Architecture • Server Supports: • Database storage • Indexing • Z39.50 access to local data • Boolean and Probabilistic Searching • Relevance Feedback • External SQL database support • Client Supports: • Programmable (Tcl/Tk – Python in C3) Graphical User Interface • Z39.50 access to remote servers • SGML & MARC formatting • Combined Client/Server CGI scripting via WebCheshire

  34. Z39.50 Overview UI Map Query Search Engine Map Results Map Query Internet Map Results Map Query UI Map Results

  35. Lecture Outline • XML and DBMS • The Grid and DBMS • The Grid • Data Grids • Grid-based DBMS

  36. Grid-based Digital Libraries • So what’s this Grid thing anyhow? • Data Grids and Distributed Storage • Grid-Based IR • Grid-Based Digital Libraries • Grid vs “Cloud” This lecture borrows heavily from presentations by Ian Foster (Argonne National Laboratory & University of Chicago), Reagan Moore and others from San Diego Supercomputer Center

  37. The Grid: On-Demand Access to Electricity Quality, economies of scale Time Source: Ian Foster

  38. By Analogy, A Computing Grid • Decouples production and consumption • Enable on-demand access • Achieve economies of scale • Enhance consumer flexibility • Enable new devices • On a variety of scales • Department • Campus • Enterprise • Internet Source: Ian Foster

  39. What is the Grid? “The short answer is that, whereas the Web is a service for sharing information over the Internet, the Grid is a service for sharing computer power and data storage capacity over the Internet. The Grid goes well beyond simple communication between computers, and aims ultimately to turn the global network of computers into one vast computational resource.” Source: The Global Grid Forum

  40. Not Exactly a New Idea … • “The time-sharing computer system can unite a group of investigators …. one can conceive of such a facility as an … intellectual public utility.” • Fernando Corbato and Robert Fano , 1966 • “We will perhaps see the spread of ‘computer utilities’, which, like present electric and telephone utilities, will service individual homes and offices across the country.” Len Kleinrock, 1967 Source: Ian Foster

  41. But, Things are Different Now • Networks are far faster (and cheaper) • Faster than computer backplanes • “Computing” is very different than pre-Net • Our “computers” have already disintegrated • E-commerce increases size of demand peaks • Entirely new applications & social structures • We’ve learned a few things about software Source: Ian Foster

  42. Computing isn’t Really Like Electricity • I import electricity but must export data • “Computing” is not interchangeable but highly heterogeneous: data, sensors, services, … • This complicates things; but also means that the sum can be greater than the parts • Real opportunity: Construct new capabilities dynamically from distributed services • Raises three fundamental questions • Can I really achieve economies of scale? • Can I achieve QoS across distributed services? • Can I identify apps that exploit synergies? Source: Ian Foster

  43. Why the Grid?(1) Revolution in Science • Pre-Internet • Theorize &/or experiment, aloneor in small teams; publish paper • Post-Internet • Construct and mine large databases of observational or simulation data • Develop simulations & analyses • Access specialized devices remotely • Exchange information within distributed multidisciplinary teams Source: Ian Foster

  44. Why the Grid?(2) Revolution in Business • Pre-Internet • Central data processing facility • Post-Internet • Enterprise computing is highly distributed, heterogeneous, inter-enterprise (B2B) • Business processes increasingly computing- & data-rich • Outsourcing becomes feasible => service providers of various sorts Source: Ian Foster

  45. The Information Grid Imagine a web of data • Machine Readable • Search, Aggregate, Transform, Report On, Mine Data – using more computers, and less humans • Scalable • Machines are cheap – can buy 50 machines with 100Gb or memory and 100 TB disk for under $100K, and dropping • Network is now faster than disk • Flexible • Move data around without breaking the apps Source: S. Banerjee, O. Alonso, M. Drake - ORACLE

  46. The Foundations are Being Laid Edinburgh Glasgow DL Newcastle Belfast Manchester Cambridge Oxford Hinxton RAL Cardiff London Soton Tier0/1 facility Tier2 facility Tier3 facility 10 Gbps link 2.5 Gbps link 622 Mbps link Other link

  47. Data Grid Problem • “Enable a geographically distributed community [of thousands] to pool their resources in order to perform sophisticated, computationally intensive analyses on Petabytes of data” • Note that this problem: • Is common to many areas of science • Overlaps strongly with other Grid problems

  48. Data Grids forHigh Energy Physics ~PBytes/sec ~100 MBytes/sec Offline Processor Farm ~20 TIPS There is a “bunch crossing” every 25 nsecs. There are 100 “triggers” per second Each triggered event is ~1 MByte in size ~100 MBytes/sec Online System Tier 0 CERN Computer Centre ~622 Mbits/sec or Air Freight (deprecated) Tier 1 FermiLab ~4 TIPS France Regional Centre Germany Regional Centre Italy Regional Centre ~622 Mbits/sec Tier 2 Tier2 Centre ~1 TIPS Tier2 Centre ~1 TIPS Caltech ~1 TIPS Tier2 Centre ~1 TIPS Tier2 Centre ~1 TIPS HPSS HPSS HPSS HPSS HPSS ~622 Mbits/sec Institute ~0.25TIPS Institute Institute Institute Physics data cache ~1 MBytes/sec 1 TIPS is approximately 25,000 SpecInt95 equivalents Physicists work on analysis “channels”. Each institute will have ~10 physicists working on one or more channels; data for these channels should be cached by the institute server Pentium II 300 MHz Pentium II 300 MHz Pentium II 300 MHz Pentium II 300 MHz Tier 4 Physicist workstations Image courtesy Harvey Newman, Caltech

  49. Grids and Open Standards Open Grid Services Arch Web services GGF: OGSI, … (+ OASIS, W3C) Multiple implementations, including Globus Toolkit X.509, LDAP, FTP, … Globus Toolkit Defacto standards GGF: GridFTP, GSI App-specific Services Increased functionality, standardization Custom solutions Time

  50. The Gridas Enabler of 21st Century Science • Entirely new approaches to enquiry based on • Deep analysis of huge quantities of data • Interdisciplinary collaboration • Large-scale simulation • Smart instrumentation • Enabled by an infrastructure that enables access to, and integration of, resources & services without regard for location

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